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A high-density, high-channel count, multiplexed µECoG array for auditory-cortex recordings.

Authors :
Escabí, Monty A.
Read, Heather L.
Viventi, Jonathan
Dae-Hyeong Kim
Higgins, Nathan C.
Storace, Douglas A.
Liu, Andrew S. K.
Gifford, Adam M.
Burke, John F.
Campisi, Matthew
Yun-Soung Kim
Avrin, Andrew E.
Van der Spiegel, Jan
Yonggang Huang
Ming Li
Jian Wu
Rogers, John A.
Litt, Brian
Cohen, Yale E.
Source :
Journal of Neurophysiology. 9/15/2014, Vol. 112 Issue 6, p1566-1583. 18p.
Publication Year :
2014

Abstract

Our understanding of the large-scale population dynamics of neural activity is limited, in part, by our inability to record simultaneously from large regions of the cortex. Here, we validated the use of a large-scale active microelectrode array that simultaneously records 196 multiplexed micro-electrocortigraphical (µECoG) signals from the cortical surface at a very high density (1,600 electrodes/cm²). We compared µECoG measurements in auditory cortex using a custom "active" electrode array to those recorded using a conventional "passive" µECoG array. Both of these array responses were also compared with data recorded via intrinsic optical imaging, which is a standard methodology for recording sound-evoked cortical activity. Custom active µECoG arrays generated more veridical representations of the tonotopic organization of the auditory cortex than current commercially available passive µECoG arrays. Furthermore, the cortical representation could be measured efficiently with the active arrays, requiring as little as 13.5 s of neural data acquisition. Next, we generated spectrotemporal receptive fields from the recorded neural activity on the active µECoG array and identified functional organizational principles comparable to those observed using intrinsic metabolic imaging and single-neuron recordings. This new electrode array technology has the potential for large-scale, temporally precise monitoring and mapping of the cortex, without the use of invasive penetrating electrodes. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00223077
Volume :
112
Issue :
6
Database :
Academic Search Index
Journal :
Journal of Neurophysiology
Publication Type :
Academic Journal
Accession number :
108658463
Full Text :
https://doi.org/10.1152/jn.00179.2013